Table of Content

28 December 2023, Volume 56 Issue 12

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Special Contribution

Impacts of Electricity Emission Factor Selection on High Energy-Consuming Industries with the Expanded National Carbon Market

Zhongtao QIU, Yanming JIN, Shenzhi XU

2023, 56(12):  1-7.  DOI: 10.11930/j.issn.1004-9649.202309106

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Electricity emission factors are widely used in carbon accounting of different subjects such as industries, enterprises and products. Due to the different resource endowments in China, the differences of regional power emission factors are more significant. The use of national, regional and provincial emission factors will have greater impacts on the indirect carbon accounting of industrial enterprises and products. It directly affects the provincial "double carbon" indicator assessment, the payment of tariffs on the export of energy-consuming products and the costs of compliance in the domestic carbon market. This study takes the electrolytic aluminum industry as an example to measure the impacts of the selection of electricity emission factors on the carbon accounting of products in energy-consuming industries. The results show that the selection of electricity emission factors needs to be tailored to the application scenarios of the accounting subject. From the perspective of promoting fairness, the national carbon emissions trading market should adopt the national average electricity emission factor. While assessing the carbon emission intensity of provincial and sub-provincial administrative regions, compiling greenhouse gas inventories of provincial and sub-provincial administrative regions, and disclosing the voluntary greenhouse gas emission reports of enterprises, priority should be given to adopting the average emission factor of electricity corresponding to the provincial power grids.

Planning, Operation and Power Transaction of Distributed Smart Grid

Review and Outlook of Autonomous Unit Planning of Distribution Network

Can CHEN, Jing WANG, Zongmin YU, Yuan MA, Yi WANG, Liangchenxi FAN, Ran DING, Hongquan LI

2023, 56(12):  9-19.  DOI: 10.11930/j.issn.1004-9649.202304096

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The development of distributed power generation, new energy storage, and adjustable load on the distribution network side increased the difficulty of ensuring secure and reliable power supply. Rational planning of autonomous units can enhance flexibility, power supply security, and ability to integrate energy at the minimum economic cost. However, existing planning methods mostly consider constraints of power supply reliability and economic efficiency, without considering resource relevance, control modes, and electricity market factors, resulting in redundant planning results and resource waste. This paper reviewed and analyzed the physical scope of autonomous units, influencing factors of capacity planning, modeling methods and solving algorithms, clarifies the physical meaning of autonomous units, analyzes the influence of source-load random uncertainty and correlation, regulation mode, electricity market policy and other factors on autonomous unit capacity planning, discusses the autonomous unit modeling method considering multiple factors, and compares the applicable conditions of different solving algorithms. Finally, the shortcomings of the current autonomous unit capacity planning were summarized, and corresponding suggestions and prospects were proposed.

A Minimized Data Collection Optimization Method for Distribution Networks Considering Multiple-Time and Compressed Candidate Sets

Zhaoxiang YUAN, Zhihong XIAO, Jing WANG, Yanling YU, Yan HUANG, Xingle GAO

2023, 56(12):  20-30.  DOI: 10.11930/j.issn.1004-9649.202307052

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At present, the insufficient observability of distribution networks leads to the lack of energy management ability of medium and low voltage distribution networks under large-scale distributed power grid connection. The minimized data collection technology for distribution networks can optimize the measurement configuration with the minimum economic cost, which plays an important role in improving the system observability. In this paper, a minimized data collection optimization method considering multiple time sections is proposed. The model of this method is solved in two stages: In the first stage, the candidate measurement set is compressed, with the Fisher information matrix (FIM) value used as the pheromone update parameter of ant colony algorithm. Since an iterative update is not required for the FIM, a significant decrease in algorithm complexity can be found. On this basis, the second stage involves a consideration of the accuracy requirement for state estimation, determining the optimal configuration scheme according to the ant colony algorithm. The comparison of schemes shows that the minimized data collection method in this paper, with a full consideration of the influence of power flow distribution changes on state estimation accuracy, realizes the intensive configuration and efficient calculation of data collection terminals, so as to ensure economical terminal investments and highly observable distribution networks.

Optimal Configuration of Distributed Energy Storage in Distribution Networks Based on Moment Difference Analysis

Donglei SUN, Yao WANG, Huiwen ZHANG, Rui LIU, Bingke SHI

2023, 56(12):  31-40.  DOI: 10.11930/j.issn.1004-9649.202306057

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With the introduction of the "double carbon" goal, the future distribution network will face a very high proportion of new energy such as photovoltaic. The increasing penetration of distributed photovoltaics in the distribution network leads to frequent issues such as voltage violations and reverse power flow. This paper proposes an optimization configuration method for distributed energy storage based on moment difference analysis, which is built upon the existing voltage regulation methods and reactive power compensation in distribution networks. The method is proposed to address situations where the on-site accommodation of distributed photovoltaic capacity is not feasible due to its large size, and the high-power return of photovoltaics causes node voltage to exceed limits. The paper introduces the concept of "photovoltaic moment" and "load moment", and subsequently presents the concept of "moment difference". It derives formulas and provides theoretical analysis of the relationship between "moment difference" and node voltage. The paper details the methods for calculating the photovoltaic moment and load moment. Based on this, a new method of energy storage optimization configuration of distribution network based on moment difference analysis is proposed. The goal is to ensure that no node in the distribution network exceeds the upper voltage limit when photovoltaic power is returned. An example of IEEE 33 node distribution system shows that compared with traditional intelligent optimization algorithms, the proposed method can directly determine the installation location of energy storage, which has high computational efficiency, accurate calculation results and strong engineering practicability.

Research on Synchronization Control of Distributed Generation Based on Second-Order Unified Model

Yan HUANG, Yingpeng HAO, Huixian WANG, Longye ZHENG, Kaizhe ZHANG, Yinliang XU

2023, 56(12):  41-50.  DOI: 10.11930/j.issn.1004-9649.202305133

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The existing grid connection controls of distributed generation inverters are mainly classified into the grid-following (GFL) control and the grid-forming (GFM) control. In this paper, with the multi-timescale separation method, the second-order unified models of GFL and GFM synchronization control are established. Based on the unified models, the small-signal stabilities of GFL and GFM control are analyzed, pointing that GFL control is compatible with strong grid, while weak grid can improve the damping ratio of GFM control. Besides, the transient stabilities of GFL and GFM are analyzed, and a general stability-enhanced method is proposed to enhance the synchronization stability. Finally, these findings are corroborated by experimental tests.

A Data-Driven Optimal Power Flow Model under Partial Observability

Penghua LI, Zhuoran SONG, Wenchuan WU

2023, 56(12):  51-57.  DOI: 10.11930/j.issn.1004-9649.202306041

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The linearized power flow (PF) model is mainly used to make the optimal power flow (OPF) problem convex. However, existing data-driven linear PF models are mostly based on complete system measurement data. Moreover, the systems are usually partially observable due to limited measuring devices for economical installation. This paper addresses the partial observability issue by proposing a data-driven linear PF model, which can be embedded in OPF. The model is robust against bad data in measurements, with its accuracy verified by numerical tests.

Economic Operation Method of Active Distribution Network Based on Blockchain and Endowment Effect

Li ZHOU, Chuanyu XIONG, Fangchao KE, Zhiwei LI, Hong ZHANG, Ran CHEN, Wanfang LIU, Yazhou YU, Liqin REN

2023, 56(12):  58-68.  DOI: 10.11930/j.issn.1004-9649.202305036

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With the large-scale integration of renewable energy, the number of participants involved in electricity transactions is increasing. The traditional centralized trading model, which is matched by the dispatching center, fails to cope with the surge of transaction data and achieve the optimal economic operation of the active distribution network. Therefore, an economic operation method of an active distribution network based on blockchain and endowment effect is proposed, which uses the decentralized, autonomous, and anonymous characteristics of blockchain to construct an electricity transaction mechanism. On this basis, users participating in demand response are regarded as "behavioral agents", and an endowment effect-based demand response model is constructed, which is more in line with users' psychological needs. The calculation results show that the proposed electricity transaction mechanism based on blockchain technology can effectively improve the efficiency of electricity transactions, and the established endowment effect-based demand response model can effectively improve the economic operation and source-load matching of the active distribution network.

Multi-Objective Cluster Classification and Voltage Control Approach for Active Distribution Network Considering Resource Reserve Degree

Jing WANG, Yi YUAN, Yinchi SHAO, Jinqi ZHANG, Ran DING, Yanjiang GONG

2023, 56(12):  69-79.  DOI: 10.11930/j.issn.1004-9649.202307070

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A multi-objective cluster classification and voltage control approach for an active distribution network considering resource reserve degree is proposed to solve the problem that the node voltage exceeds the limit after the high penetration rate of distributed photovoltaic (PV) power generation is connected to the distribution network. Firstly, by considering the influence of its own regulation ability on cluster coupling relationship and global control ability when distributed PV power generation is connected, a multi-dimensional cluster classification indicator considering resource reserve degree is established. Then, the K-means clustering algorithm is used to improve the discrete particle swarm optimization (DPSO) algorithm to convert the cluster classification into an optimization solution problem. Then, a voltage control model of the active distribution network cluster is built. With the reactive/active power of the dominant node as the control object, the sequential action and power of distributed PV power generation are determined. Finally, the power grid of a rooftop distributed PV development pilot in a county is taken as a simulation example, and the voltage control effect, system network loss, and PV utilization rate under different schemes are analyzed. The correctness and effectiveness of the voltage control approach proposed in this paper are verified.

Evaluation of Distributed Photovoltaic Maximum Hosting Capacity for Distribution Network Considering Dispatchable Potential of 5G Base Station

Yao DUAN, Chong GAO, Ran CHENG, Yaxiong WU, Ye HUANG, Zhiwen LIU

2023, 56(12):  80-85, 99.  DOI: 10.11930/j.issn.1004-9649.202309018

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A method for evaluate the maximum hosting capacity of distributed photovoltaic for distribution network considering the schedulable potential of 5G base station is proposed. Firstly, construct a power load demand model for 5G base station and analyze the schedulable potential of 5G base station's own energy storage; Then, establish the distributed photovoltaic maximum hosting capacity evaluation model of distribution network considering the dispatchable potential of 5G base station; Subsequently, auxiliary variables are introduced and the model is subjected to second-order cone relaxation to construct a linearized model for distributed PV maximum hosting capacity assessment. Finally, the improved IEEE 33 bus distribution network is used to evaluate the distributed PV maximum hosting capacity of distribution network under different scenarios. The results show that considering the dispatchable potential of 5G base station can effectively improve the maximum hosting capacity of distributed new energy in distribution network.

Key Technologies for Improving the Resilience of Power Systems

A Distributed Resilience Enhancement Strategy for Multi-microgrids Based on System of Systems Architecture

Linxinyan LIN, Junpeng ZHU, Yue YUAN

2023, 56(12):  87-99.  DOI: 10.11930/j.issn.1004-9649.202304051

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To enhance the ability of multi-microgrid systems to cope with extreme scenarios, a distributed resilience enhancement strategy for multi-microgrids based on system of systems(SoS) architecture is proposed. Firstly, the energy exchange process of the multi-microgrid systems is modeled based on the SoS architecture, and the distributed optimization algorithm is used to solve the model, which ensures the privacy of user information. Secondly, the minimum load-shedding problem of the system is solved with both economic optimality and frequency stability as the goals, and the internal needs of the sub-microgrids are specifically met while pursuing the overall operation effect of the system. Finally, the synchronous alternating direction multiplier method based on a dynamic multiplier update strategy is adopted to solve the problem of parameter selection of the distributed algorithm, thus improving the convergence and practicability of the algorithm. Case study verified the effectiveness of the proposed model and algorithm.

Review and Prospect of Distribution Network Resilience Assessment and Improvement Based on CiteSpace

Yan WU, Guangzheng WANG

2023, 56(12):  100-112, 137.  DOI: 10.11930/j.issn.1004-9649.202306119

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This paper aims to reveal the research trends in the field of distribution network resilience research through CiteSpace-based visual analysis, and provide a reference for systematically grasping the theoretical context and development trends of distribution network resilience, as well as for subsequent related research. The study shows that domestic scholars pay attention to improving the reliability of distribution network, risk assessment methods, impact of electric vehicles, power quality assurance, smart grid construction and energy storage technology improvement. In addition to above-said issues, foreign scholars also pay attention to demand response, active distribution network and optimal configuration , etc., and the research focus has gradually shifted from technical methods to emerging technologies and management methods. Through keywords clustering analysis, four major research directions, including domestic distribution network assessment, planning and design, power supply reliability and new energy grid integration, three major research fields, including foreign artificial intelligence and smart grid, renewable energy, power system resilience and reliability are reviewed. Finally, the highly cited literature in the field is analyzed, which can provide important inspiration for field development and problem solving.

Flexible Control Device Configuration Planning for Transmission Network Resilience Enhancement

Li LI, Xin HUANG, Tianyuan XU, Yue CHEN, Qiuyu LU, Yinguo YANG, Yang LIU, Yu ZHU, Gengfeng LI, Chengcheng SHAO

2023, 56(12):  113-126.  DOI: 10.11930/j.issn.1004-9649.202310024

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To enhance power system resilience and ensure the capability of transmission grid to handle the events of low-probability but high impacts, a flexible control device configuration planning framework for transmission network is proposed based on robust optimization theory. This framework fully considers the optimal synergy among different categories of control devices, including optimal transmission switch (OTS) under remote switch configuration, transmission line reinforcement devices and energy storage systems (ESS), aiming to minimize the operational costs while reducing the economic losses caused by extreme events. Firstly, a two-stage robust planning model is constructed based on the load duration curves (LDC), considering typical daily interruptions of transmission lines and renewable energy output fluctuations. And then, the modified Nested Column-and-Constraints Generation (NCCG) algorithm is employed to solve the proposed model, and relevant acceleration strategies are utilized to enhance the computational efficiency. Finally, a simulation analysis is conducted using the IEEE 24-bus system to validate the planning synergy among different flexible control devices and to assess the effectiveness of the proposed model.

Risk Limiting Based Resilient Operation Method for Power Grid

Xiyue WANG, Hao ZHANG, Chaoyi PENG

2023, 56(12):  127-137.  DOI: 10.11930/j.issn.1004-9649.202307045

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Under the background of construction of the new power system, the integration of a large amount of renewable energy into the existing grid poses significant challenges to the dispatch and operation mode of power grid. In order to address the risk of load shedding caused by the power fluctuation and uncertainty of renewable energy on real-time power balance in the grid, we propose a resilient operation model for the grid based on risk limiting theory (RLB). To solve the problem of solving probabilistic constraints, a solution is provided to enhance the operational resilience of the grid. By deriving three intermediate state models of RLB and their analytical solutions, we present an iterative RLB solution algorithm based on intermediate state models and provide a rigorous proof of its global optimality. Finally, based on the IEEE 6-node system and an actual 25981-node regional grid examples, we analyze the relationship between system flexibility, prediction accuracy, and system resilience, and it is concluded that improving the operational resilience of the new power system is premised on sufficient system flexibility and prediction accuracy.

Entity and Event Recognition Method for Power Grid Fault Handling Plan Based on UIE Framework

Junbo PI, Shixiong QI, Wenduo SUN, Xiansi LOU, Jiandong WO, Yue ZHANG, Tao JIANG, Lianfei SHAN

2023, 56(12):  138-146.  DOI: 10.11930/j.issn.1004-9649.202307076

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The power grid fault handling plan is obvious in regional differentiation and the nested entities are complex, so it is difficult to accurately structure the fault handling plan only by entity type identification. An entity and event recognition method for power grid fault handling plan based on an universal information extraction (UIE) framework is proposed. Firstly, an entity marking method for fault handling plan based on syntactic analysis is proposed to generate fault handling plan marking entity. Then, the ERNIE 3.0 encoding and double-pointer decoding module are used to replace the generative model in the UIE framework, and the mapping relationship between entity and entity labels of fault handling plan and the nested entity relationship are trained through adjusting the hyper-parameters of the UIE framework. Finally, the complex nested plan entities are combined to obtain the plan event based on the syntactic structure. Through verification by the plans of different regional power grid dispatch and control centers, the proposed method has higher entity and event recognition accuracy for fault handling plans than other algorithms. It can accurately identify the fault handling strategies and recovery strategies in the plan, and provide support for the improvement of the regional power grid elasticity in the case of fault.

Planning and Operation Technologies for Multi-Energy Systems in Low-Carbon Parks

Optimal Allocation of Energy Storage Capacity in High Proportion Clean Energy Parks Considering Demand Response

Zhaojun JIANG, Yue XIANG, Zhukui TAN, Yongtao GUO, Yang WANG, Ke ZHOU

2023, 56(12):  147-155, 163.  DOI: 10.11930/j.issn.1004-9649.202302038

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In order to improve the level of clean energy consumption and the economy of energy storage allocation in parks, an optimal allocation method for energy storage capacity of high-proportion clean energy parks considering demand response is proposed. Firstly, the photovoltaic, wind turbine, and energy storage power models are established. Secondly, a demand response mechanism considering the participation of rigid, transferable and interruptible loads is designed to realize the transfer of loads under a certain time scale. Then, taking the lowest total net present cost of the system as the optimization goal, an energy storage economic allocation model is established with consideration of the constraints such as grid-connected power fluctuations and charge & discharge limits. Case study verifies the effectiveness of the proposed method, and the results show that compared to the traditional method, the proposed allocation method can effectively reduce the economic cost of the system and improve the level of clean energy consumption.

Optimal Operation Strategy for Virtual Power Plant Considering Regulation Market and External Demand Response

Weiliang HUANG, Zhipeng SU, Xinyi LIANG, Tao CHEN, Li WANG, Liang ZHOU

2023, 56(12):  156-163.  DOI: 10.11930/j.issn.1004-9649.202309024

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The participation of virtual power plant (VPP) in power grid demand response has become an important means for peak load shaving in new power system. It is critical to consider how to improve the profitability of VPPs in the electricity market. Therefore, This paper proposes an optimal operation strategy for VPP considering regulation market and external demand response. Firstly, the regulation market (RM) and demand response exchange market (DRXM) models are established. Secondly, considering the flexibility of external demand response (EDR), an operation decision framework is established for VPP with EDR to participate in the day-ahead and regulation market. Acting as an aggregator of multiple EDR suppliers, the DRXM provides EDR services to VPP to reduce the imbalance penalty of RM and to improve the economy of VPP. And then, a two-level VPP optimization operation model is established. In the upper level, the VPP maximizes its profits through participating in DRXM to reduce the RM penalty; in the lower level, the distribution system operator minimizes its operating cost through cleaning up the day-ahead market and regulation market deviation. The KKT conditions are used to transform the optimization model into a linear single-layer problem for solution. Finally, the improved IEEE 33-node distribution network system is used for case study, which verifies the effectiveness of the proposed optimal operation strategy in improving the VPP’s benefit ability and the effects of different EDR service ratios on VPP decision-making.

Cooperative Operation Optimization for Integrated Energy Microgrid Groups Based on Federated Learning

Mingfeng XUE, Xiaobo MAO, Hao XIAO, Yibin ZHOU, Xiaowei PU, Wei PEI

2023, 56(12):  164-173.  DOI: 10.11930/j.issn.1004-9649.202302034

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In the current cooperative operation of multi-agent integrated energy microgrids, the centralized optimization strategy has been experiencing the contradiction of agent privacy protection and parameter sharing, while in the distributed optimization, the optimization model needs to be simplified and approximated extensively such that the global optimal solution is not guaranteed. With regard to these challenges, this paper proposes a coordinated and optimized operation method for multi-agent integrated energy microgrids based on federated learning to achieve global optimum without compromising the agent privacy. Firstly, the equivalent interactive characteristic packaging model of each integrated energy microgrid is built based on the gated recurrent unit deep learning network and then uploaded to the cloud. Secondly, on condition of no invasion into the internal privacy data of each microgrid, the equivalent model of each individual microgrid is encrypted, and then consolidated in the cloud for federated learning. Thirdly, according to the results of cloud federation learning, the packaging model of interaction characteristics of each integrated energy microgrid at the edge is modified and updated iteratively until the loss function converges. In this way the global collaborative optimization operation of the integrated energy microgrids can be achieved under privacy protection. Finally, the feasibility and effectiveness of the proposed method are verified through case studies simulating a typical integrated energy microgrids. The results show that this method can realize the fast and efficient optimization operation of the integrated energy micro-group and effectively protect the data privacy of all participants.

Optimal Dispatch of Virtual Power Plant Considering Stepped Carbon Trading and Comprehensive Demand Response

Zhipeng SU, Li WANG, Xinyi LIANG, Tao CHEN, Shunqi ZENG, Zhiwen YU

2023, 56(12):  174-182.  DOI: 10.11930/j.issn.1004-9649.202308094

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Under the goal of "double carbon", the virtual power plant (VPP) with multi-energy coupling and collaborative operation can effectively reduce the carbon emissions and improve the economic benefits of the system. In order to further reduce VPP carbon emissions and tap the demand side adjustable potential a VPP optimal scheduling model was proposed considering stepped carbon trading and integrated demand response. Firstly, based on the stepped carbon trading mechanism, considering the constraints of each VPP component, a VPP model is established to participate in the carbon trading market. Secondly, the demand response is divided into price demand response and alternative demand response, and the demand response model are constructed respectively. Finally, considering the energy purchase cost, system operation cost and stepped carbon transaction cost, a VPP low-carbon economic operation model is established with the goal of maximizing the benefits of VPP in a scheduling cycle, and the effectiveness of the model was verified by numerical analysis.

Power System

Protection Loop Error Measurement Based on Factor Analysis and Statistics Technology

Yawen YI, Chuanbin JIANG, Shiyu GONG, Xiaoyuan QIN, Jingpu ZHAO, Zhenxing LI

2023, 56(12):  183-190.  DOI: 10.11930/j.issn.1004-9649.202309022

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In order to improve the reliability of the protection measurement circuit and ensure the safe operation of the power system, which requires the measurement error of the protection device to be solved in time. An error evaluation method based on factor analysis and statistical techniques is constructed for the protection measurement circuit in this paper. Based on the principle that there is strong linear correlation between the three phase data, the three-phase current obtained by the protection measurement circuit is analyzed and the error starting criterion is established. Based on the results of factor analysis, three classical statistics and control threshold in statistical techniques are used to locate the error source, and the evaluation accuracy of error less than 5% is achieved. The effectiveness and accuracy of this method are proved by simulation results.

Fault Recovery Strategy of Distribution Networks Based on Quantum Firefly Algorithm

Juan LI, Jiaming WANG, Sudi XU, Yunlong JIANG, Xiong YANG

2023, 56(12):  191-198.  DOI: 10.11930/j.issn.1004-9649.202309079

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Existing distribution network fault recovery strategy tends to be inefficient and locally convergent for high penetrated distributed photovoltaic grid connection. Hence in this paper, a distribution network fault recovery strategy is proposed based on quantum firefly algorithm . The objective function is constructed in terms of a master-slave dual objective optimization to minimize both the load loss and network losses, and corresponding fault recovery model with distributed photovoltaic grid connection is established by taking into account of the constraints. To overcome the drawbacks of the standard firefly algorithm, quantum encoding and quantum rotation gates were applied to enhance the optimization efficiency and global search capability of the firefly algorithm such that the total solution time can be greatly shortened. Next from the fault recovery model solved after proposed algorithm, by controlling the on-off status of the circuit breakers in the distribution network system, the lost load can be restored as much as possible to ensure the restoration of power supply to critical loads, while minimizing network losses. Finally, case studies were conducted on the IEEE 33 bus system to verify the feasibility and advantages of the proposed method.

Multi-Stage Coordinated Planning Method for Transmission Network and Energy Storage Considering Carbon Trading Cost

Qiang LI, Yao WANG, Yingying HU, Xiaoming ZHENG, Linna ZHANG, Yongming JING

2023, 56(12):  199-205.  DOI: 10.11930/j.issn.1004-9649.202309095

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The coordinated development of transmission network and energy storage is an important way to build a new type of power system. Traditional transmission and storage coordination planning often overlooks the error in the probability of clustering new energy output scenarios such as wind power, and the planning results are conservative. For this reason, this article first generates a typical scenario set by clustering the load demand and wind farm output under the annual cycle, and considers the error of scenario probability to establish an uncertain set of scenario probability distribution based on 1-norm and ∞ norm. Then, a multi-stage coordinated distributed robust programming model for transmission and storage is established with comprehensive objectives of transmission line investment cost, energy storage investment cost, operation cost, and carbon trading cost. The column and constraint generation (C&CG) algorithm is used to transform the multi-stage coordinated distributed robust programming model for transmission and storage into an iterative solution of the main and sub problems. The superiority of the proposed multi-stage coordinated planning method for transmission and storage was verified on an improved IEEE-30 node system.

Detection of Electricity Theft by Low Voltage Users with Zero Power Consumption Based on Water-Electricity Correlation Information

Nian ZOU, Meifang WEI, Sheng SU, Yingjun ZHENG, Wenqing ZHOU

2023, 56(12):  206-216.  DOI: 10.11930/j.issn.1004-9649.202211098

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It is hard to obtain the effective information on electricity consumption behaviors of zero-power consumption users among low-voltage residential electricity theft users who are easily confused with vacant house owners, which is a special problem for electricity theft detection. Based on the strong correlation between water and electricity data of residential users, a zero-power user electricity theft detection method is proposed based on water-electricity correlation information. Firstly, the relationship between electricity and water consumption data of residential users is analyzed. Then, a maximal information model of users' daily electricity consumption and daily water consumption is constructed, and the maximum information coefficient (MIC) at different time scales is calculated to measure the information correlation. Thirdly, the user's maximal information coefficient is clustered, and the samples that deviate significantly from the cluster are identified as the suspected electricity theft users with weak water-electricity correlation. When the electricity consumption of the suspected electricity theft users is zero, they are identified as the electricity theft users with zero power consumption. The test examples of two distribution areas show that the proposed method can effectively detect the electricity theft users with zero power consumption and guide the on-site electricity theft detection work.

Transmission Tower Tilt State Recognition Based on Parameter Optimization of VMD-SVD and LSTM

Long ZHAO, Guanru WEN, Zhicheng LIU, Peng YUAN, Xinsheng DONG

2023, 56(12):  217-226, 237.  DOI: 10.11930/j.issn.1004-9649.202302065

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To address the problems of high difficulty and poor accuracy in extracting the structural state information of transmission towers, a transmission tower tilt state recognition solution is proposed based on the northern goshawk optimized variational mode decomposition (NGO-VMD) and long short-term memory (LSTM) neural network. The problem to determine the VMD parameters is solved by NGO, and it is demonstrated that the decomposed intrinsic mode function (IMF) components of each order can effectively extract the modal information of the tower structure. In order to make the information features more obvious, the singular value decomposition (SVD) of IMF components is performed, and it is found that the singular values of each order component have more obvious differences in different states of the tower. Finally, the LSTM neural network is introduced for feature classification to form a fault diagnosis model. A 110 kV cathead-type tower is used to verify the proposed model, and the results show that the proposed method can achieve an accuracy of 96.68% in identification of tower tilting state. Compared with other methods, this solution has the advantages of higher efficiency, stronger stability and better accuracy.

New Energy

Model and Algorithm of Cooperative Optimization Decomposition for Short-Term Contract Electricity Considering Wind Power Uncertainty

Lingjie LIU, Jikeng LIN

2023, 56(12):  227-237.  DOI: 10.11930/j.issn.1004-9649.202305031

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Most of the existing contract electricity decomposition methods do not take into account the impact of wind power uncertainty and do not coordinate with the generation plan for optimization, resulting in their insufficient execution when the contract is due. A new cooperative optimization decomposition model and algorithm of short-term contract electricity is therefore proposed with consideration of the wind power uncertainty and maintenance plans. Firstly, a cooperative optimization decomposition model and algorithm of short-term contract electricity is constructed with the objective of minimization of the generation cost, contract deviation cost and low-quality wind power risk cost, to obtain the decomposed daily contract electricity. And then, based on the day-ahead and intraday short-term and ultra-short-term load and wind power forecast information, the day-ahead robust generation plan model and algorithm and the intraday redispatch model and algorithm are constructed respectively with consideration of the contract completion degree, to realize the full accommodation of wind power and full execution of the daily contract electricity with the premise of power load to be fully supplied and the security constraints to be met. Furthermore, the uncompleted daily contract electricity is fulfilled through rolling updating the subsequent daily contract electricity to ensure the full execution of the short contract electricity when the contract is due. The results of case study have demonstrated the feasibility and superiority of the proposed model and algorithm.

Control Strategy and Optimal Configuration of Active-Support-Grid Type Decentralized Energy Storage System for Wind Farms

Cheng LI, Jie ZHANG, Ke SHI, Minghua XUE, Bo FENG

2023, 56(12):  238-247.  DOI: 10.11930/j.issn.1004-9649.202305132

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A decentralized energy storage system for renewable energy stations has the characteristics of small capacity, wide dispersion, flexible deployment, and convenient expansion, which reduces the hidden dangers of accidents caused by battery aggregation and avoids the problem of high land acquisition and supporting construction costs. It can not only ensure refined management for nodes but also achieve cluster control, helping renewable energy stations improve grid-related operation performance, reduce assessment costs, and improve power generation efficiency. First of all, based on the principle of "decentralized layout and centralized control", a decentralized energy storage cluster control strategy is proposed, which virtualizes the decentralized energy storage into a centralized energy storage form and reasonably distributes power instructions according to the state of charge and state of health of energy storage. Secondly, according to the grid interconnection requirements, a coordinated control strategy for wind-storage systems based on frequency modulation priority is designed. By referring to the detailed rules of Jiangsu Province, a decentralized energy storage configuration optimization model is proposed to actively support the grid. The calculation example shows that the allocation of a certain scale of the energy storage system can reduce the assessment cost and improve the grid-related operation performance.

Evaluation of Renewable Energy Consumption Capacity in Power Grid Considering the Synergistic Effect of Wind-Photovoltaic- Hydro-Thermal Power

Weimin ZHENG, Yangqing DAN, Chenxuan WANG, Jiahui WU, Yunfeng ZHU

2023, 56(12):  248-254.  DOI: 10.11930/j.issn.1004-9649.202305105

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This paper studies the problem of power grid absorption capacity evaluation, and an evaluation method of renewable energy consumption capacity of power grid considering wind-photovoltaic-hydro-thermal power multi-energy coordination is proposed. Firstly, the framework of wind-photovoltaic-hydro-thermal power multi-energy cooperative system is constructed. Then, the definition of the operational risk of renewable energy acceptance is given, and the operational risk model of renewable energy is established. Finally, based on the two-stage robust optimization theory, the evaluation model of renewable energy consumption capacity of power grid considering wind-photovoltaic-hydro-thermal power multi-energy cooperation is proposed, and the column and constraint generation (C&CG) algorithm is used to solve the problem. The results of example show that the proposed model can control the uncertainty set of renewable energy output and assess the renewable energy consumption capacity of power grid effectively.

Energy Transition

Effect Analysis and Promotion Path Design for Transformation from Energy Consumption "Dual Control" to Carbon "Dual Control"

Fang TANG, Hongcai DAI, Ning ZHANG, Yue WU, Meimei XUE, Rui CHEN

2023, 56(12):  255-261.  DOI: 10.11930/j.issn.1004-9649.202310070

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The transformation from energy consumption "dual control" to carbon "dual control" system will bring about the surge in demand for renewable energy, and increase the level of new energy development and terminal electrification, which, at present, may increase the pressure of new energy consumption and power supply. The integrated economy-energy-environment model estimates the effects of the transformation of "dual control" system on the appraised total amount and relevant indicators. The key of the transformation from energy consumption "dual control" to carbon "dual control" lies in reasonable determination of the controlling indicators, comprehensive improvement of basic conditions, and order coordination of implementation scopes. The study shows that the later stage of the "Fourteenth Five-Year Plan" is the early stage of the transformation of the dual control system, during which the construction of basic conditions need to be strengthened, and pilot demonstrations shall be conducted in several provinces and cities. The early stage of the "Fifteenth Five-Year Plan" is the middle stage of the transformation, during which the appraised indicators are mainly carbon emission intensity, supplemented by the total carbon emission. The later stage of the "Fifteenth Five-Year Plan" is the period of completion of the transformation, during which the basic conditions are available, and the appraised indicators realizes the comprehensive transition of energy to carbon, and the industries incorporated into the carbon market are removed from the "dual control" of administrative divisions.

Study on Low-Carbon Transition Path of Power Industry in Gansu Province Considering Hydrogen Energy Demand

Xueqiang ZHANG, Long DONG, Dong WANG

2023, 56(12):  262-272.  DOI: 10.11930/j.issn.1004-9649.202211012

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Hydrogen energy is an important direction in the development of clean energy and has a wide range of application prospects in the fields of power, industry, transportation and building heating, etc. The comprehensive utilization of hydrogen energy is crucial to the low-carbon transformation of the power industry. This paper forecasts the hydrogen energy demand in various fields based on the SVR model and various social data, and uses the energy conversion relationship between power consumption and hydrogen production to equivalently replace the hydrogen energy, while forecasting the investment cost of various types of equipment; the planning model is established with the forecast data, the initial installation situation and carbon emission target as inputs, and the development scale of various power sources, the proportion of installed power and carbon emission as outputs; taking Gansu Province as an example, the planning model is analysed. The impact of hydrogen energy participation in the low-carbon transformation of the power industry is explored, providing reference for the planning of the low-carbon transformation path of the power industry in Gansu Province.